Various methods for localizing mobile objects are known from the prior art based on measured features of a radio network. The radio network therein includes a multiplicity of stationary base stations that transmit signals or, as the case may be, receive signals wirelessly. A mobile object able likewise to receive or, as the case may be, transmit signals wirelessly moves within the radio network. The mobile object's location can then be determined by way of corresponding features or, as the case may be, parameters of the fields transmitted by the base stations or, as the case may be, mobile object. For example the signal strength of the field transmitted by the mobile object, which field is measured by the base stations or, as the case may be, the signal strength of the fields of the individual base stations at the mobile object's location can be used for determining the location. The mobile object can be localized also by way of the propagation time of field signals or, as the case may be, wave-propagation directions. Localizing methods are therein employed that are based on triangulation or on theoretical or adapted wave-propagation models, or on what is termed pattern matching. Pattern matching is suitable particularly for localizing within rooms or buildings and employs a feature map which for a multiplicity of grid points in the room contains corresponding features of the radio network in the form of, for instance, signal field strengths when the mobile object is located at a corresponding grid point. The mobile object's location can then be estimated by comparing the features in the feature map with the radio network's actually measured features.
As well as for localizing a mobile object, a radio network's measured features can be used also for generating the aforementioned feature map. Methods that describe generating corresponding feature maps by means of learning techniques are known therein from the prior art. Instances of such techniques can be found in publications [1], [2], and [3].
With known methods in which features of a radio network are processed for localizing a mobile object or generating feature maps, those signals are evaluated in an individual computing unit that can be integrated in, for example, the mobile object or a base station. It is possible also to use a separate, central computing unit to which all the measured features are conveyed for evaluating. It has here proved disadvantageous that the entire process will be terminated if the computing unit fails, with any already acquired information then being lost. Extending that method to cover larger localizing areas by adding more base stations or mobile objects is subject moreover to reservations as that will greatly increase the necessary computing power which will hence no longer be provided in a reasonable time by an individual computing unit.